Variance from covariance

Statistics.var Method

Statistics.var(ce::AbstractCovarianceEstimator, X::MatNum; dims::Int = 1, kwargs...)

Compute the variance vector from the diagonal of the covariance matrix.

This method extracts the diagonal of the covariance matrix returned by Statistics.cov(ce, X; dims = dims, kwargs...) and reshapes it into a row or column vector depending on dims.

Arguments

• ce: Covariance estimator.

• X: Data matrix of asset returns (observations × assets).

• dims: Dimension along which to perform the computation.

• kwargs...: Additional keyword arguments passed to the covariance estimator.

Returns

• var::Matrix{<:Number}: Variance vector, shaped as (1, N) if dims == 1 or (N, 1) if dims == 2.

Related

• AbstractCovarianceEstimator

• std(ce::AbstractCovarianceEstimator, X::MatNum; dims::Int = 1, kwargs...)

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Statistics.std Method

Statistics.std(ce::AbstractCovarianceEstimator, X::MatNum; dims::Int = 1, kwargs...)

Compute the standard deviation vector from the diagonal of the covariance matrix.

This method extracts the diagonal of the covariance matrix returned by Statistics.cov(ce, X; dims = dims, kwargs...), takes the element-wise square root, and reshapes it into a row or column vector depending on dims.

Arguments

• ce: Covariance estimator.

• X: Data matrix of asset returns (observations × assets).

• dims: Dimension along which to perform the computation.

• kwargs...: Additional keyword arguments passed to the covariance estimator.

Returns

• sd::Matrix{<:Number}: Standard deviation vector, shaped as (1, N) if dims == 1 or (N, 1) if dims == 2.

Related

• AbstractCovarianceEstimator

• var(ce::AbstractCovarianceEstimator, X::MatNum; dims::Int = 1, kwargs...)

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